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Controlling large Boolean networks with single-step perturbations

MOTIVATION: The control of Boolean networks has traditionally focussed on strategies where the perturbations are applied to the nodes of the network for an extended period of time. In this work, we study if and how a Boolean network can be controlled by perturbing a minimal set of nodes for a single...

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Autores principales: Baudin, Alexis, Paul, Soumya, Su, Cui, Pang, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612811/
https://www.ncbi.nlm.nih.gov/pubmed/31510648
http://dx.doi.org/10.1093/bioinformatics/btz371
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author Baudin, Alexis
Paul, Soumya
Su, Cui
Pang, Jun
author_facet Baudin, Alexis
Paul, Soumya
Su, Cui
Pang, Jun
author_sort Baudin, Alexis
collection PubMed
description MOTIVATION: The control of Boolean networks has traditionally focussed on strategies where the perturbations are applied to the nodes of the network for an extended period of time. In this work, we study if and how a Boolean network can be controlled by perturbing a minimal set of nodes for a single-step and letting the system evolve afterwards according to its original dynamics. More precisely, given a Boolean network (BN), we compute a minimal subset [Formula: see text] of the nodes such that BN can be driven from any initial state in an attractor to another ‘desired’ attractor by perturbing some or all of the nodes of [Formula: see text] for a single-step. Such kind of control is attractive for biological systems because they are less time consuming than the traditional strategies for control while also being financially more viable. However, due to the phenomenon of state-space explosion, computing such a minimal subset is computationally inefficient and an approach that deals with the entire network in one-go, does not scale well for large networks. RESULTS: We develop a ‘divide-and-conquer’ approach by decomposing the network into smaller partitions, computing the minimal control on the projection of the attractors to these partitions and then composing the results to obtain [Formula: see text] for the whole network. We implement our method and test it on various real-life biological networks to demonstrate its applicability and efficiency. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-66128112019-07-12 Controlling large Boolean networks with single-step perturbations Baudin, Alexis Paul, Soumya Su, Cui Pang, Jun Bioinformatics Ismb/Eccb 2019 Conference Proceedings MOTIVATION: The control of Boolean networks has traditionally focussed on strategies where the perturbations are applied to the nodes of the network for an extended period of time. In this work, we study if and how a Boolean network can be controlled by perturbing a minimal set of nodes for a single-step and letting the system evolve afterwards according to its original dynamics. More precisely, given a Boolean network (BN), we compute a minimal subset [Formula: see text] of the nodes such that BN can be driven from any initial state in an attractor to another ‘desired’ attractor by perturbing some or all of the nodes of [Formula: see text] for a single-step. Such kind of control is attractive for biological systems because they are less time consuming than the traditional strategies for control while also being financially more viable. However, due to the phenomenon of state-space explosion, computing such a minimal subset is computationally inefficient and an approach that deals with the entire network in one-go, does not scale well for large networks. RESULTS: We develop a ‘divide-and-conquer’ approach by decomposing the network into smaller partitions, computing the minimal control on the projection of the attractors to these partitions and then composing the results to obtain [Formula: see text] for the whole network. We implement our method and test it on various real-life biological networks to demonstrate its applicability and efficiency. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-07 2019-07-05 /pmc/articles/PMC6612811/ /pubmed/31510648 http://dx.doi.org/10.1093/bioinformatics/btz371 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Ismb/Eccb 2019 Conference Proceedings
Baudin, Alexis
Paul, Soumya
Su, Cui
Pang, Jun
Controlling large Boolean networks with single-step perturbations
title Controlling large Boolean networks with single-step perturbations
title_full Controlling large Boolean networks with single-step perturbations
title_fullStr Controlling large Boolean networks with single-step perturbations
title_full_unstemmed Controlling large Boolean networks with single-step perturbations
title_short Controlling large Boolean networks with single-step perturbations
title_sort controlling large boolean networks with single-step perturbations
topic Ismb/Eccb 2019 Conference Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612811/
https://www.ncbi.nlm.nih.gov/pubmed/31510648
http://dx.doi.org/10.1093/bioinformatics/btz371
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